1. Field of the Invention
Embodiments of the disclosure relate in general to the field of computers and similar technologies and, in particular, to software utilized in this field. Still more particularly, it relates to the automated allocation of resources to migrated logical partitions.
2. Description of the Related Art
The growing demand for information management continues to drive the development of progressively more sophisticated information processing environments. In recent years, it has become common to maximize the utilization of information processing system (IPS) resources by logically partitioning the computer platform hardware that comprises a central processor complex (CPC). A logical partition (LPAR) within a CPC allows multiple copies of a single operating system (OS) or multiple heterogeneous operating systems to be simultaneously run on a single IPS platform. An LPAR, within which an operating system image runs, is assigned a non-overlapping subset of the platform's resources. These platform resources include one or more architecturally distinct processors, regions of system memory, and input/output (I/O) adapter bus slots.
Current solutions for partition management enable LPARs to share needed resources in the CPC while maintaining their separately defined computing environments. The resulting efficient access and management of IPS resources not only reduces operations and system management costs, but also maintains needed capacity by responding to the dynamic needs of user applications. Logical partitioning now enables administrators to support dynamic resource allocation across multiple operating system environments by moving processors, memory and I/O between LPARs as their respective workloads change. For example, processors allocated to a test partition can be moved to a production partition in periods of peak demand and then moved back to the test partition when demand subsides. Likewise, memory resources can be moved from an idle partition to a partition experiencing heavy paging. Similarly, underutilized processor, memory and I/O resources can be moved from their respective partitions into a pool of resources for reallocation to newly created partitions. As a result, the implementation of partitioning in IPS environments has now evolved to enable a single, consolidated view, access and utilization of available computing resources in a network, regardless of their location.
Prior art approaches exist for the automated allocation of IPS resources across LPARs within a CPC. For example, an automated resource manager (ARM) can dynamically allocate IPS resources by working collaboratively with a hardware management console (HMC). The HMC creates, starts, stops and terminates partitions and provides the ARM with partition and resource utilization information. By monitoring the provided resource utilization information, the ARM can dynamically reallocate resources from partitions with a lower demand to partitions with a high demand, thereby improving the overall resource utilization of the system. Additional IPS resource management and utilization flexibility can be achieved by migrating LPARS between CPCs, such as in a networked computing environment. For example, workloads can be balanced by migrating an LPAR from a CPC operating at capacity to a CPC with excess capacity. Since IPS resources are constrained to the physical CPC, IPS resources allocated to an LPAR do not migrate with it, freeing them for reallocation to the remaining LPARs. However, since a migration can occur on a live, running partition, the ARM is not aware that the migration has taken place and continues to allocate IPS resources to the partition, even though they are not being used. As a result, the ARM is unable to automatically reallocate these unused IPS resources to other LPARs within the CPC until they are released from their allocation to the migrated partition through manual intervention.